Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog – Page 6775

Here’s what we already know about Ford’s electric F-150.

Ford is set to unveil its next major electric vehicle, the F-150 Lightning, at 9:30PM ET on Wednesday, May 19th. But this isn’t just another EV event. An electric version of the automaker’s iconic F-series pickup truck is a very big deal for Ford, for the auto world, for car buyers, and even for the US economy.

Ford is very proud of its F-series trucks, and for good reason. It’s the bestselling truck in the US for 44 years. It’s also the bestselling vehicle in the country, period. According to Edmunds, F-series trucks are the most popular vehicle in 30 out of 50 states in the US.

Continue reading “Ford F-150 Lightning: what to expect from the automaker’s first electric pickup truck” | >

Photon counting and reliable photon number resolving, until now, only partially available utilizing esoteric EMCCD technology in highly controlled laboratory environments, is now possible with a compact form-factor camera, operating at room temperature — with the additional benefits of higher resolution and speed. “The ability to do photon counting at room temperature is a game changer for our research efforts in Astrophysics and Quantum Information Science,” said Dr. Don Figer, Director of Center for Detectors and the Future Photon Initiative in the College of Science, Rochester Institute of Technology.

Read more | >

These clever semiconductors make our internet-connected world go round. In addition to iPhones and PlayStations, they underpin key national infrastructure and sophisticated weaponry.

But recently there haven’t been enough of them to meet demand.

The reasons for the ongoing global chip shortage, which is set to last into 2022 and possibly 2023, are complex and multifaceted. However, nations are planning to pump billions of dollars into semiconductors over the coming years as part of an effort to sure up supply chains and become more self-reliant, with money going toward new chip plants, as well as research and development.

Read more | >

Researchers with the BrainGate Collaboration have deciphered the brain activity associated with handwriting: working with a 65-year-old (at the time of the study) participant with paralysis who has sensors implanted in his brain, they used an algorithm to identify letters as he attempted to write them; then, the system displayed the text on a screen; by attempting handwriting, the participant typed 90 characters per minute — more than double the previous record for typing with a brain-computer interface.

So far, a major focus of brain-computer interface research has been on restoring gross motor skills, such as reaching and grasping or point-and-click typing with a computer cursor.

Read more | >

WASHINGTON — The Tyvak-0130 rideshare payload that flew to orbit May 15 on a SpaceX Falcon 9 carries a miniature space telescope for possible commercial use.

The technology was developed by Tyvak Nano-Satellite Systems and the Lawrence Livermore National Laboratory under a four-year agreement to advance compact telescopes for commercial applications, Tyvak’s CEO Christian “Boris” Becker said in an interview with SpaceNews.

Becker, a retired U.S. Navy rear admiral, was recently named chief executive of Tyvak, a satellite manufacturer in Irvine, California, owned by Terran Orbital.

Read more | >

Machine learning algorithms have gained fame for being able to ferret out relevant information from datasets with many features, such as tables with dozens of rows and images with millions of pixels. Thanks to advances in cloud computing, you can often run very large machine learning models without noticing how much computational power works behind the scenes.

But every new feature that you add to your problem adds to its complexity, making it harder to solve it with machine learning algorithms. Data scientists use dimensionality reduction, a set of techniques that remove excessive and irrelevant features from their machine learning models.

Dimensionality reduction slashes the costs of machine learning and sometimes makes it possible to solve complicated problems with simpler models.

Read more | >